wehub-resource-sync
50 lines
1.9 KiB
Python
50 lines
1.9 KiB
Python
# Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import unittest
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from paddlenlp.transformers import YuanTokenizer
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class YuanTokenizationTest(unittest.TestCase):
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def test_extract_non_learnable_parts(self):
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models_with_templates = [
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"IEITYuan/Yuan2-2B",
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"IEITYuan/Yuan2-51B",
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"IEITYuan/Yuan2-102B",
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]
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dummy_conversastions = [
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["Q.", "A."],
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["Q.A.", "A."],
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["Q?", "A!"],
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]
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decode_outputs = [
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["Q.<n>", "A.<n>"],
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["Q.A.<n>", "A.<n>"],
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["Q?<n>", " A!<sep>"], # notify there is an extra space
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]
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context_data = {}
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context_data["is_training"] = True
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for model_id in models_with_templates:
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tokenizer = YuanTokenizer.from_pretrained(model_id)
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if tokenizer.chat_template is None:
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continue
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conversation_result: list[tuple[list[int], list[int]]] = tokenizer.encode_chat_inputs(
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dummy_conversastions,
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context_data=context_data,
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)
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for idx, round in enumerate(conversation_result["conversations"]):
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self.assertEqual(tokenizer.decode(round[0]), decode_outputs[idx][0])
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self.assertEqual(tokenizer.decode(round[1]), decode_outputs[idx][1])
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